WikiSkill Paper: Compiling Agent Experience into Persistent Knowledge for Skill Evolution
tuvllms · x · 2026-09-01
WikiSkill introduces a framework that decouples raw agent experience from executable skills using a persistent knowledge layer (wiki) to consolidate insights over time. Experiments show consistent performance gains across model sizes (up to +23.9% average accuracy at 27B) and effective cross-family skill transfer (e.g., Qwen skills improving Gemma on math and reasoning tasks). This demonstrates that skill evolution complements model scaling, allowing smaller models with transferred skills to outperform larger baselines.
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